Skip to main content

An investigation of marker-passing algorithms for analogue retrieval

  • Scientific Sessions
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1010))

Abstract

If analogy and case-based reasoning systems are to scale up to very large case bases, it is important to analyze the various methods used for retrieving analogues to identify the features of the problem for which they are appropriate. This paper reports on one such analysis, a comparison of retrieval by marker passing or spreading activation in a semantic network with Knowledge-Directed Spreading Activation, a method developed to be well-suited for retrieving semantically distant analogues from a large knowledge base. The analysis has two complementary components: (1) a theoretical model of the retrieval time based on a number of problem characteristics, and (2) experiments showing how the retrieval time of the approaches varies with the knowledge base size. These two components, taken together, suggest that KDSA is more likely than SA to be able to scale up to retrieval in large knowledge bases.

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. A. Aamodt. Explanation-driven case-based reasoning. In S. Wess, K. Althoff, and M. Richter, editors, Topics in Case-Based Reasoning. Springer-Verlag, 1994.

    Google Scholar 

  2. J. Anderson. The Architecture of Cognition. Harvard University Press, 1983.

    Google Scholar 

  3. J. Anderson and R. Thompson. Use of analogy in a production system architecture. In S. Vosniadou and A. Ortony, editors, Similarity and Analogical Reasoning, pages 267–297. Cambridge University Press, 1989.

    Google Scholar 

  4. H. Bunke and B. Messmer. Similarity measures for structured representations. In S. Wess, K. Althoff, and M. Richter, editors, Topics in Case-Based Reasoning. Springer-Verlag, 1994.

    Google Scholar 

  5. P. Cunningham, B. Smyth, D. Finn, and E. Cahill. Retrieval issues in real-world CBR applications: How far can we go with discrimination-nets? In IJCAI Workshop on Re-Use of Designs, 1993.

    Google Scholar 

  6. C. Knoblock. Automatically Generating Abstractions for Problem Solving. PhD thesis, Carnegie Mellon University, 1991.

    Google Scholar 

  7. J. Kolodner. Case-Based Reasoning. Morgan-Kaufmann, 1993.

    Google Scholar 

  8. L. Rau. Knowledge organization and access in a conceptual information system. Information Processing and Management, 23:269–283, 1987.

    Google Scholar 

  9. P. Thagard, K. Holyoak, G. Nelson, and D. Gochfeld. Analog retrieval by constraint satisfaction. Artificial Intelligence, 46:259–310, 1990.

    Google Scholar 

  10. P. Winston. Learning and reasoning by analogy. Communications of the ACM, 23:689–703, 1980.

    Google Scholar 

  11. M. Wolverton. Retrieving Semantically Distant Analogies. PhD thesis, Stanford University, 1994.

    Google Scholar 

  12. M. Wolverton and B. Hayes-Roth. Retrieving semantically distant analogies with knowledge-directed spreading activation. In AAAI-94, 1994.

    Google Scholar 

  13. M. Wolverton and B. Hayes-Roth. Finding analogues for innovative design. In Third Int'l Conference on Computational Models of Creative Design, 1995.

    Google Scholar 

  14. R. Zito-Wolf and R. Alterman. A framework and an analysis of current proposals for the case-based organization and representation of procedural knowledge. In AAAI-93, 1993.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Manuela Veloso Agnar Aamodt

Rights and permissions

Reprints and permissions

Copyright information

© 1995 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wolverton, M. (1995). An investigation of marker-passing algorithms for analogue retrieval. In: Veloso, M., Aamodt, A. (eds) Case-Based Reasoning Research and Development. ICCBR 1995. Lecture Notes in Computer Science, vol 1010. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60598-3_32

Download citation

  • DOI: https://doi.org/10.1007/3-540-60598-3_32

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60598-0

  • Online ISBN: 978-3-540-48446-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics